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Multisystem inflammatory syndrome in children (MIS-C) is a rare complication of SARS-CoV-2 infection that can result in serious illness in the paediatric population but our understanding of this syndrome is in its infancy. Translational studies in 2020 leveraging immune profiling have laid the foundation to enable further discovery in MIS-C.
Since the outset of the COVID-19 pandemic, numerous risk factors for severe disease have been identified. Whether patients with rheumatic diseases, especially those receiving DMARDs, are at an increased risk of SARS-CoV-2 infection or severe COVID-19 disease remains unclear, although epidemiological studies are providing some insight.
Interest in therapies for psoriatic arthritis (PsA) has increased in response to recognition that many patients remain undiagnosed and are inadequately treated. In 2020, advances in PsA treatments have included phase III trials of an IL-23 inhibitor, head-to-head trials of IL-17 inhibition against TNF inhibition and updated EULAR treatment guidelines.
In inflammatory arthritides, such as rheumatoid arthritis (RA), synovial cells acquire aggressive and disruptive phenotypes that lead to joint disease. Three studies published in 2020 have described phenotypic variation in synovial cells, offering a novel perspective on the potential to resolve pathology and augment treatment options for patients with RA.
Immune checkpoint inhibitors, which are used to treat many types of cancer, can cause syndromes similar to rheumatic diseases known as immune-related adverse events (irAEs). In 2020, several studies illustrated the clinical heterogeneity of rheumatic irAEs and highlighted their substantial effect on morbidity and mortality.
Machine learning and high-throughput technologies hold promise for the classification, diagnosis and treatment of patients with rheumatic diseases, with the ultimate goal of precision medicine. Several studies in 2019 highlight the feasibility and clinical utility of using machine learning in rheumatology to stratify patients and/or predict treatment responses.
